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Negative life experiences are well-established risk factors for mental health problems, yet evidence from low- and middle-income countries remains limited. Many studies also overlook area-level factors that may influence these relationships. This study aimed to examine the association between negative life events and depression among individuals in Indonesia, accounting for both individual and area-level characteristics. This cross-sectional study used data from 31,446 individuals aged 15 years and older who participated in the Indonesia Family Life Survey Wave 5 (IFLS-5), conducted in 2014-2015. Depression was assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10), a validated instrument measuring depressive symptoms during the past week. Negative life events, including chronic illness (self or family member), natural disasters or accidents, and deaths of family members within the past year, were evaluated. Multilevel logistic regressions accounted for the hierarchical data structure and adjusted for demographic, socioeconomic, behavioural, and district-level characteristics. The prevalence of depression was 23%. Experiencing one negative life event increased the odds of depression (adjusted odds ratio [AOR] = 1.22, 95% confidence interval [CI]: 1.15-1.30), while two or more events further elevated the odds (AOR = 1.55, 95% CI: 1.32-1.83), adjusted for covariates. Individually, chronic illness (AOR = 1.25, 95% CI: 1.17-1.33), natural disasters or accidents (AOR = 1.41, 95% CI: 1.15-1.73), and deaths of family members (AOR = 1.14, 95% CI: 1.03-1.26) were significantly associated with depression. Multiple and specific negative life events substantially increase the risk of depression among Indonesians. These findings highlight the importance of integrating culturally sensitive mental health interventions within community and healthcare settings.

Background Indonesia has implemented a series of healthcare reforms including its national health insurance scheme (Jaminan Kesehatan Nasional, JKN) to achieve universal health coverage. However, there is evidence of inequitable healthcare utilization in Indonesia, raising concerns that the poor might not be benefiting fully from government subsidies. This study aims to identify factors affecting healthcare utilization in Indonesia. Methods This study analysed cross-sectional survey data collected by the “Equity and Health Care Financing in Indonesia” (ENHANCE) Study. Andersen’s behavioural model of health services use was adopted as a framework for understanding healthcare utilization in Indonesia. Sociodemographic variables were categorized into predisposing, enabling and need factors. Outcome measures included the utilization of primary and secondary health services. Multi-level logistic regression models were run to examine factors associated with each type of health service utilization. Results Of the 31,864 individuals included in the ENHANCE survey, around 14% had used outpatient services in the past month. Fewer than 5% of the study population had visited hospitals for inpatient care and about 23% used maternal and child health services in the past 12 months. Age, gender and self-rated health were key determinants of health services utilization. No significant differences in primary care utilization were found among people with different insurance status, but people who received subsidised premiums under the JKN were more likely to receive primary care from public health facilities and less likely from private health facilities. Compared to people who pay JKN insurance premiums themselves, the uninsured and those whose premiums were subsidised by the government were less likely to visit public and private hospitals when other factors were controlled. Conclusion This study demonstrates that the distribution of healthcare utilization in Indonesia is largely equitable as predisposing factors (age and gender) and health need were found to greatly influence the utilization of different types of health services. However, enabling factors such as health insurance status were also found to be associated with inequity in utilization of hospital services. Further policy actions regarding resource allocation and health service planning are warranted to achieve a more equitable pattern of health service use in Indonesia.

Background The Indonesian National Health Insurance Agency (BPJS-K) administers one of the largest single-payer healthcare systems in the world, with 95% of Indonesia’s population registered by December 2023. Since 2019, BPJS-K has provided sample data representing 1% of insured individuals. Despite its potential, the BPJS-K sample data remains underutilised in research. Methods This study provides an overview of the BPJS-K dataset, including research that has used it, its structure, contents, and key variables from 2015 to 2020. We present descriptive statistics for the sample, including age and gender distributions, insurance membership type, healthcare visits, diagnoses, referrals, and associated tariffs. We illustrate the dataset’s potential applications for health policy analysis and its strengths and limitations. Results The BPJS-K sample data broadly represents the Indonesian population, as evidenced by comparisons to census data. Regional disparities in healthcare utilisation were observed, with lower service access in Eastern Indonesia. Key variables include diagnoses, such as acute respiratory infections (6% of the visits, the highest in primary healthcare), and reimbursement information for visits to referral healthcare providers and for non-capitation services to primary healthcare providers. The data has the potential to facilitate health policy analysis, given its longitudinal nature and possible linkage to other data. However, current shortcomings, such as limited socio-economic information and quality of diagnostic information, should be considered. Conclusion The BPJS-K sample data offers potential for longitudinal and cross-sectional health policy research. However, further improvements in data quality, diagnostic recording, accessibility, and linkage to socio-economic data are recommended to optimise its usefulness for research.

Background Depression has become the leading cause of disease burden in low- and middle-income countries. However, evidence on the determinants of depression in those countries has been limited. This study aims to identify the factors in individual and area levels associated with depression using existing nationally representative data in Indonesia. Methods Multilevel mixed-effects logistic regression models were performed on various national-scale Indonesian cross-sectional surveys and Indonesian Population Census to estimate those associations. We included adults aged 18 + who participated in the National Basic Health Research 2018 in this study. Depression was measured using the Mini International Neuropsychiatric Interview (MINI). Individual level variables include demographic characteristics, socioeconomic status, history of diseases, health behaviours, healthcare accessibility, and familial history of psychosis. District-level variables include the availability of health providers and professionals, regional gross domestic product, and the happiness index. Results We found that individual-level factors, i.e., education, occupation, marital status, economic status, comorbidities, health behaviours, and difficulty with healthcare access were associated with the risk of depression. Happiness index as district-level factor, is related to the odds of depression. District-level factors, including the availability of general practitioners and mental health professionals and the density of healthcare providers, had no significant association with depression. The measured variables provided modest explanatory value overall. Conclusion Individual-level factors are associated with depression among adults in Indonesia. Among the district level factors, only happiness index is related to depression. These results strengthen previous studies which stated determinants at the individual level are an important factor in depression. Therefore, effective prevention programs in mental health need to target both individuals and families.

Background Indonesia implemented one of the world’s largest single-payer national health insurance schemes (the Jaminan Kesehatan Nasional or JKN) in 2014. This study aims to assess the incidence of catastrophic health spending (CHS) and its determinants and trends between 2018 and 2019 by which time JKN enrolment coverage exceeded 80%. Methods This study analysed data collected from a two-round cross-sectional household survey conducted in ten provinces of Indonesia in February–April 2018 and August–October 2019. The incidence of CHS was defined as the proportion of households with out-of-pocket (OOP) health spending exceeding 10% of household consumption expenditure. Chi-squared tests were used to compare the incidences of CHS across subgroups for each household characteristic. Logistic regression models were used to investigate factors associated with incurring CHS and the trend over time. Sensitivity analyses assessing the incidence of CHS based on a higher threshold of 25% of total household expenditure were conducted. Results The overall incidence of CHS at the 10% threshold fell from 7.9% to 2018 to 4.4% in 2019. The logistic regression models showed that households with JKN membership experienced significantly lower incidence of CHS compared to households without insurance coverage in both years. The poorest households were more likely to incur CHS compared to households in other wealth quintiles. Other predictors of incurring CHS included living in rural areas and visiting private health facilities. Conclusions This study demonstrated that the overall incidence of CHS decreased in Indonesia between 2018 and 2019. OOP payments for health care and the risk of CHS still loom high among JKN members and among the lowest income households. More needs to be done to further contain OOP payments and further research is needed to investigate whether CHS pushes households below the poverty line.

Background Many countries implementing pro-poor reforms to expand subsidized health care, especially for the poor, recognize that high-quality healthcare, and not just access alone, is necessary to meet the Sustainable Development Goals. As the poor are more likely to use low quality health services, measures to improve access to health care need to emphasise quality as the cornerstone to achieving equity goals. Current methods to evaluate health systems financing equity fail to take into account measures of quality. This paper aims to provide a worked example of how to adapt a popular quantitative approach, Benefit Incidence Analysis (BIA), to incorporate a quality weighting into the computation of public subsidies for health care. Methods We used a dataset consisting of a sample of households surveyed in 10 provinces of Indonesia in early-2018. In parallel, a survey of public health facilities was conducted in the same geographical areas, and information about health facility infrastructure and basic equipment was collected. In each facility, an index of service readiness was computed as a measure of quality. Individuals who reported visiting a primary health care facility in the month before the interview were matched to their chosen facility. Standard BIA and an extended BIA that adjusts for service quality were conducted. Results Quality scores were relatively high across all facilities, with an average of 82%. Scores for basic equipment were highest, with an average score of 99% compared to essential medicines with an average score of 60%. Our findings from the quality-weighted BIA show that the distribution of subsidies for public primary health care facilities became less ‘pro-poor’ while private clinics became more ‘pro-rich’ after accounting for quality of care. Overall the distribution of subsidies became significantly pro-rich (CI = 0.037). Conclusions Routine collection of quality indicators that can be linked to individuals is needed to enable a comprehensive understanding of individuals’ pathways of care. From a policy perspective, accounting for quality of care in health financing assessment is crucial in a context where quality of care is a nationwide issue. In such a context, any health financing performance assessment is likely to be biased if quality is not accounted for.

Background As the global shift toward non-communicable diseases overlaps with the unfinished agenda of confronting infectious diseases in low- and middle-income countries, epidemiological links across both burdens must be recognized. This study examined the non-communicable disease-infectious disease overlap in the specific comorbidity rates for key diseases in an occupational cohort in Papua, Indonesia. Methods Diagnosed cases of ischaemic heart disease, stroke, hypertension, diabetes (types 1 and 2), chronic obstructive pulmonary disease, asthma, cancer, HIV and AIDS, tuberculosis, and malaria were extracted from 22,550 patient records (21,513 men, 1037 women) stored in identical electronic health information systems from two clinic sites in Papua, Indonesia. Data were collected as International Classification of Diseases, 10th Revision, entries from records spanning January-December 2013. A novel application of Circos software was used to visualize the interconnectedness between the disease burdens as overlapping prevalence estimates representing comorbidities. Results Overall, NCDs represented 38 % of all disease cases, primarily in the form of type 2 diabetes ( n  = 1440) and hypertension ( n  = 1398). Malaria cases represented the largest single portion of the disease burden with 5310 recorded cases, followed by type 2 diabetes with 1400 cases. Tuberculosis occurred most frequently alongside malaria (29 %), followed by chronic obstructive pulmonary disease (19 %), asthma (17 %), and stroke (12 %). Hypertension-tuberculosis (4 %), tuberculosis-cancer (4 %), and asthma-tuberculosis (2 %) comorbidities were also observed. Conclusions The high prevalence of multimorbidity, preponderance of non-communicable diseases, and extensive interweaving of non-communicable and infectious disease comorbidities highlighted in this cohort of mining workers in Papua, Indonesia reflect the markedly double disease burden increasingly plaguing Indonesia and other similar low- and middle-income countries – a challenge with which their over-stretched, under-resourced health systems are ill-equipped to cope. Integrated, person-centered treatment and control strategies rooted in the primary healthcare sector will be critical to reverse this trend.

Doc number: A18